Collected observations from travels among universities


Invited seminars and job interviews offer a unique opportunity to learn (and remember) what grad school is like and how universities work. You get to have a lot of intentional sit-down conversations on a wide variety of topics. Spending time meeting new people and learning new stuff rocks. And when you chat with other people about themselves, and their work, labs and universities, you have a chance to put your own way of doing things in perspective.

I’ve had a few such opportunities in the past month. There were a number of recurring conversational themes and undercurrents. During these visits, you get to have conversations to learn not just about all kinds of research, but about how people chose the directions that led to their current trajectories. And, you often learn about how personal lives shape our research directions and priorities, both by design and by hap.

Here are some of the highlights. None of these observations are shocking news by any measure. But I was struck by the obviousness of these ideas and the frequency with which they emerged, even when I wasn’t looking for them:

  • Research universities are no longer primarily oriented towards training excellent scientists. They are now primarily oriented towards teaching students how to publish and to get grants. If a grad student develops the desire to become an excellent practitioner of science, this is probably going to emerge from the undergraduate experience.
  • Anybody currently building a future in the quantitative sciences needs to learn how to write code to promote their own research success. Being able to manage and analyze super-duper huge datasets (bioinformatics) is really useful.
  • High quantity data will never be a substitute for high quality data.
  • People need to get off their goddamn phones.
  • Genomics is now at the point when all flavors of biologists are in a practical position to figure out heritable mechanisms accounting for phenomena involving organisms in nature. For many kinds of questions, any species can now be a model system.
  • Most ecological theories are ephemeral, and are either myopic or wrong. The parenting of popular, ephemeral and myopic theories is the prevailing route to success.
  • It’s difficult to maintain the presence of mind to recognize the power of one’s own authority.
  • In ecology and evolutionary biology, women fall out of academic careers most heavily in the transition phase between from Ph.D. to faculty. Lots of parties are at fault, but the ones that seem to be the most significant are some senior faculty (of both genders) and some spouses. Deans have many opportunities to proactively make positive changes, but that rarely happens.
  • The number of students who want to do serious, long-term, field biology in the service of contemporary research questions has sharply declined. This limits our potential to answer some major wide open questions in biology.
  • Universities that maintain a strong faculty actively keep their professors from going on the market in search of greener pastures. Universities would not lose valued faculty members as often as they do, if they actually supported faculty commensurate with the degree to which they are valued. Once someone is driven to look for a new faculty job on the market, then it’s impossible to not take a great offer seriously, even when there are many good reasons to not move.
  • The beauty of life – both in biodiversity and our relations with fellow humans – is immense beyond words. Humanity might be ugly, but people are gorgeous.

12 thoughts on “Collected observations from travels among universities

  1. I like this blog very much. I cam across it by accident. It’s almost entirely about a country which is not mine and a subject that I have not studied, but it nevertheless contains gems of wisdom that even I can recognise. And there are a number here, even for someone in the UK. My only query is whether Bioinformatics is just a matter of writing code. I have a future daughter-in-law who has a PhD in the subject, She certainly can write code but to a complete outsider her expertise in handling massive data sets, seems to require in addition the ability to understand the way the data work and are likely to be linked, and the algorithms necessary to produce short cuts without which not even the massive computers at her disposal would be able to do what she wants them to do.

    • I’m not much good for either coding or bioinformatics, but I’ll amplify on what I wrote a bit anyway. Coding has lots of uses for things other than bioinformatics, especially many other kinds of statistics that don’t require massive datasets, and for modeling. However, I think bioinformatics requires coding if it’s done well. I think. I imagine dealing with genomic data within a species and for interspecific interactions, phylogenetics, and large-scale ecological datasets all require different skill sets but also all involve being able to look at a haystack and identify every single piece of hay.

  2. Wait, you needed to travel to other universities to realize that people should get off their phones? :-)

    • AND their laptops AND their f**king iPads! Bugs the hell out me when people are sitting in seminars or committee meetings and tap-tap-tapping away, checking emails or correcting manuscripts, and not having the common courtesy to actually listen to what’s being said.

      Rant over. It’s been a long day…….

      • If it makes you feel any better Jeff, some of them may be taking notes on your talk. At the ESA this year, it suddenly seemed to have become much more common for audience members to be using tablets or laptops during talks. And while a lot of them were working on their own stuff while listening with half an ear, a lot of them were taking notes on the talk. Wouldn’t venture a guess as to the percentage in each category…

        • Yes, same in my student classes, often they are taking notes electronically. But I suppose if they were writing by hand they could be making shopping lists or composing poetry :-)

      • This afternoon, I decided to dump a prospective undergrad just because he kept tapping away at his iPad during a lab meeting, instead of being engaged in the discussion. Definitely not taking notes.

  3. “Research universities are no longer primarily oriented towards training excellent scientists. They are now primarily oriented towards teaching students how to publish and to get grants.”

    Hm. I am not sure one can do the latter consistently without being the former.

  4. More seriously, Terry, do you see a link between the 2nd, 3rd and 9th points? I get a sense from talking to some PhD students and early career researchers that they feel there’s enough data out there to enable them to address questions for the rest of their career: they don’t need to collect any more, just rework existing data in ever-more sophisticated ways. Although I’ve been involved with meta and synthetic analyses myself, as an old-school field biologist that saddens and worries me.

    • I think there is a link. The problem of not having high quality data is tied to a lack of the right fieldwork. Having a ton of genomic data that’s not wedded to a detailed understanding of what actually happens in nature stifles progress or leads to conclusions that are mere artifacts of experimentation. Because we will always be working to understand how things evolve, and how the environment shapes the biology of organisms, there is always a place for doing detailed studies in the field, somewhere outdoors. Field biologists will become more valued as we are becoming more rare, as long as we keep up the skills that keep us relevant.

  5. This idea (“Research universities are no longer primarily oriented towards training excellent scientists. They are now primarily oriented towards teaching students how to publish and to get grants”) explains so much. Thanks.

    Also the lack of longterm fieldwork is probably tied to the lack of longterm jobs and/or funding. Can’t blame the students. They’ve been told to diversify and be flexible with respect to location.

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